ddw: Durbin Watson Distribution

In desk: Didactic Econometrics Starter Kit

Durbin Watson Distribution

Description

Calculates density values of the null distribution in the Durbin Watson test. Uses the saddlepoint approximation by Paolella (2007).

Usage

ddw(x, mod, data = list())

Arguments

x	quantile value(s) at which the density should be determined.
mod	estimated linear model object, formula (with argument data specified), or model matrix.
data	if mod is a formula then the name of the corresponding dataframe has to be specified here.

Details

The Durbin Watson Null-Distribution depends on values of the exogenous variables. That is why it must be calculated from each specific data set, respectively.

Value

Numerical density value(s).

References

Durbin, J. & Watson, G.S. (1950): Testing for Serial Correlation in Least Squares Regression I. Biometrika 37, 409-428.

Paolella (2007): Intermediate Probability - A Computational Approach, Wiley.

See Also

dw.test, pdw.

Examples

filter.est <- ols(sales ~ price, data = data.filter)
ddw(x = c(0.9, 1.7, 2.15), filter.est)

desk documentation built on May 29, 2024, 6:05 a.m.